GOOGLE

Google Local Campaigns How-To

Published

4 years ago

April 9, 2020

Looking for a way to drive customers through the front door? Welcome to the world of Google Local campaigns.

Designed to promote your businesses’ stores across Search, Maps, YouTube, and the Display Network, you simply add a few lines of text and let Google do the rest. This overview will include what requirements are needed before being able to run these campaigns and how to set up a campaign.

Basic Requirements:

It almost goes without saying but you’re going to need a storefront that accepts foot traffic. From there you’ll need to be able to track store visit conversions which does include some minimum requirements. According to Google:

Have multiple physical store locations in eligible countries. Ask your account representative if store visit conversions are available in your location.
Receive thousands of ad clicks and viewable impressions.
Have a Google My Business account linked to your Google Ads account.
Create each of your store locations in your Google My Business account.
Have at least 90% of your linked locations verified in Google My Business.
Ensure location extensions are active in your account.
Have sufficient store visits data on the backend to attribute to ad click or viewable impressions traffic and pass our user privacy thresholds.

Google tracks store visits by utilizing a phone’s GPS history to match if someone visited your store after seeing an ad.

The next major step is ensuring you have your Google my Business locations or affiliate locations linked with Google Ads and accurate.

Once you’ve completed all the necessary steps, you should see the objective to drive Local traffic populate when you’re looking at creating a new campaign.

How to Build a Campaign:

This is a smart campaign so building a campaign is pretty easy. Our main levers are campaign budget and ad assets.

When you go to create your campaign, you’ll be greeted by the familiar goal screen. You’ll click on the local store visits and promotions option to start building.

Campaign objective setting for Local Campaigns.

You don’t have many levers to pull but you can opt into creating location groups. This is helpful if you have regional budgets or know that performance differs between areas. Think of this in a similar to product feed segmentation. Cluster like locations together but it’s not necessary or something you’d want to do for every single business.

In the next step, you set campaign budget, language targeting, and you do have the ability to show a product feed if you want to display physical inventory.

Finally, we are brought to the ad creation section. These are basic ads that Google manages and manipulates out to various networks. I recommend testing a wide variety of ideas beyond what you would in traditional search. You want to grab people’s attention and drive them to visit your store. That’s a much larger ask than clicking on your website!

These are simple ads as you can see. Images and videos are important so be sure to use imagery that is eye-catching. If someone is searching for pizza places by them, it never hurts to show a pizza ready to satiate their hunger!

From there, I encourage constant testing to ensure you’re continually driving more people to your stores. If you want even more granular data, adjust the in-store visit conversion action to be your average order value.

Possible Tests:

While limited in campaign creation, there are a number of tests you can run to continually nudge performance in a positive direction. Audience targeting is an easy first step. Break out people who have visited your website recently or test out in-market audiences.

Another great option would be testing the landing page on your website. If you’re a retail store, land people directly on a sales page. If you’re a restaurant, try the menu.

Driving in-store traffic doesn’t work for every business but it can be a valuable tool to ensure your brick and mortar store sees steady traffic.

Related Topics:Display Google Ads Search YouTube

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AI

Exploring the Evolution of Language Translation: A Comparative Analysis of AI Chatbots and Google Translate

Published

2 months ago

February 26, 2024

Max

A Comparative Analysis of AI Chatbots and Google Translate

According to an article on PCMag, while Google Translate makes translating sentences into over 100 languages easy, regular users acknowledge that there’s still room for improvement.

In theory, large language models (LLMs) such as ChatGPT are expected to bring about a new era in language translation. These models consume vast amounts of text-based training data and real-time feedback from users worldwide, enabling them to quickly learn to generate coherent, human-like sentences in a wide range of languages.

However, despite the anticipation that ChatGPT would revolutionize translation, previous experiences have shown that such expectations are often inaccurate, posing challenges for translation accuracy. To put these claims to the test, PCMag conducted a blind test, asking fluent speakers of eight non-English languages to evaluate the translation results from various AI services.

The test compared ChatGPT (both the free and paid versions) to Google Translate, as well as to other competing chatbots such as Microsoft Copilot and Google Gemini. The evaluation involved comparing the translation quality for two test paragraphs across different languages, including Polish, French, Korean, Spanish, Arabic, Tagalog, and Amharic.

In the first test conducted in June 2023, participants consistently favored AI chatbots over Google Translate. ChatGPT, Google Bard (now Gemini), and Microsoft Bing outperformed Google Translate, with ChatGPT receiving the highest praise. ChatGPT demonstrated superior performance in converting colloquialisms, while Google Translate often provided literal translations that lacked cultural nuance.

For instance, ChatGPT accurately translated colloquial expressions like “blow off steam,” whereas Google Translate produced more literal translations that failed to resonate across cultures. Participants appreciated ChatGPT’s ability to maintain consistent levels of formality and its consideration of gender options in translations.

The success of AI chatbots like ChatGPT can be attributed to reinforcement learning with human feedback (RLHF), which allows these models to learn from human preferences and produce culturally appropriate translations, particularly for non-native speakers. However, it’s essential to note that while AI chatbots outperformed Google Translate, they still had limitations and occasional inaccuracies.

In a subsequent test, PCMag evaluated different versions of ChatGPT, including the free and paid versions, as well as language-specific AI agents from OpenAI’s GPTStore. The paid version of ChatGPT, known as ChatGPT Plus, consistently delivered the best translations across various languages. However, Google Translate also showed improvement, performing surprisingly well compared to previous tests.

Overall, while ChatGPT Plus emerged as the preferred choice for translation, Google Translate demonstrated notable improvement, challenging the notion that AI chatbots are always superior to traditional translation tools.

Source: https://www.pcmag.com/articles/google-translate-vs-chatgpt-which-is-the-best-language-translator

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GOOGLE

Google Implements Stricter Guidelines for Mass Email Senders to Gmail Users

Published

2 months ago

February 13, 2024

Entireweb News Bot

Beginning in April, Gmail senders bombarding users with unwanted mass emails will encounter a surge in message rejections unless they comply with the freshly minted Gmail email sender protocols, Google cautions.

Fresh Guidelines for Dispatching Mass Emails to Gmail Inboxes In an elucidative piece featured on Forbes, it was highlighted that novel regulations are being ushered in to shield Gmail users from the deluge of unsolicited mass emails. Initially, there were reports surfacing about certain marketers receiving error notifications pertaining to messages dispatched to Gmail accounts. Nonetheless, a Google representative clarified that these specific errors, denoted as 550-5.7.56, weren’t novel but rather stemmed from existing authentication prerequisites.

Moreover, Google has verified that commencing from April, they will initiate “the rejection of a portion of non-compliant email traffic, progressively escalating the rejection rate over time.” Google elaborates that, for instance, if 75% of the traffic adheres to the new email sender authentication criteria, then a portion of the remaining non-conforming 25% will face rejection. The exact proportion remains undisclosed. Google does assert that the implementation of the new regulations will be executed in a “step-by-step fashion.”

This cautious and methodical strategy seems to have already kicked off, with transient errors affecting a “fraction of their non-compliant email traffic” coming into play this month. Additionally, Google stipulates that bulk senders will be granted until June 1 to integrate “one-click unsubscribe” in all commercial or promotional correspondence.

Exclusively Personal Gmail Accounts Subject to Rejection These alterations exclusively affect bulk emails dispatched to personal Gmail accounts. Entities sending out mass emails, specifically those transmitting a minimum of 5,000 messages daily to Gmail accounts, will be mandated to authenticate outgoing emails and “refrain from dispatching unsolicited emails.” The 5,000 message threshold is tabulated based on emails transmitted from the same principal domain, irrespective of the employment of subdomains. Once the threshold is met, the domain is categorized as a permanent bulk sender.

These guidelines do not extend to communications directed at Google Workspace accounts, although all senders, including those utilizing Google Workspace, are required to adhere to the updated criteria.

Augmented Security and Enhanced Oversight for Gmail Users A Google spokesperson emphasized that these requisites are being rolled out to “fortify sender-side security and augment user control over inbox contents even further.” For the recipient, this translates to heightened trust in the authenticity of the email sender, thus mitigating the risk of falling prey to phishing attempts, a tactic frequently exploited by malevolent entities capitalizing on authentication vulnerabilities. “If anything,” the spokesperson concludes, “meeting these stipulations should facilitate senders in reaching their intended recipients more efficiently, with reduced risks of spoofing and hijacking by malicious actors.”

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GOOGLE

Google’s Next-Gen AI Chatbot, Gemini, Faces Delays: What to Expect When It Finally Launches

Published

5 months ago

December 4, 2023

Max

In an unexpected turn of events, Google has chosen to postpone the much-anticipated debut of its revolutionary generative AI model, Gemini. Initially poised to make waves this week, the unveiling has now been rescheduled for early next year, specifically in January.

Gemini is set to redefine the landscape of conversational AI, representing Google’s most potent endeavor in this domain to date. Positioned as a multimodal AI chatbot, Gemini boasts the capability to process diverse data types. This includes a unique proficiency in comprehending and generating text, images, and various content formats, even going so far as to create an entire website based on a combination of sketches and written descriptions.

Originally, Google had planned an elaborate series of launch events spanning California, New York, and Washington. Regrettably, these events have been canceled due to concerns about Gemini’s responsiveness to non-English prompts. According to anonymous sources cited by The Information, Google’s Chief Executive, Sundar Pichai, personally decided to postpone the launch, acknowledging the importance of global support as a key feature of Gemini’s capabilities.

Gemini is expected to surpass the renowned ChatGPT, powered by OpenAI’s GPT-4 model, and preliminary private tests have shown promising results. Fueled by significantly enhanced computing power, Gemini has outperformed GPT-4, particularly in FLOPS (Floating Point Operations Per Second), owing to its access to a multitude of high-end AI accelerators through the Google Cloud platform.

SemiAnalysis, a research firm affiliated with Substack Inc., expressed in an August blog post that Gemini appears poised to “blow OpenAI’s model out of the water.” The extensive compute power at Google’s disposal has evidently contributed to Gemini’s superior performance.

Google’s Vice President and Manager of Bard and Google Assistant, Sissie Hsiao, offered insights into Gemini’s capabilities, citing examples like generating novel images in response to specific requests, such as illustrating the steps to ice a three-layer cake.

While Google’s current generative AI offering, Bard, has showcased noteworthy accomplishments, it has struggled to achieve the same level of consumer awareness as ChatGPT. Gemini, with its unparalleled capabilities, is expected to be a game-changer, demonstrating impressive multimodal functionalities never seen before.

During the initial announcement at Google’s I/O developer conference in May, the company emphasized Gemini’s multimodal prowess and its developer-friendly nature. An application programming interface (API) is under development, allowing developers to seamlessly integrate Gemini into third-party applications.

As the world awaits the delayed unveiling of Gemini, the stakes are high, with Google aiming to revolutionize the AI landscape and solidify its position as a leader in generative artificial intelligence. The postponed launch only adds to the anticipation surrounding Gemini’s eventual debut in the coming year.

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